“Everything that living things do can be understood in terms of jigglings and wigglings of atoms.” Richard Feynman's remarks in the early 1960’s summarize what is today widely accepted, namely, that biological processes can be described by the dynamics of biomolecules. Molecular dynamics (MD) simulation, in this regard, is the main methodology employed in structural biology to explore the dynamical behavior of macromolecules at a microscopic level. Aided by MD, researchers have been able, for instance, to resolve atomic structures of multi-protein complexes from cryo-EM densities, thus unveiling the atomistic details of enzymatic mechanisms and characterize the binding of small molecules to proteins. To achieve all this, the capabilities of MD packages are constantly evolving, providing a multitude of complex simulation and analysis techniques, e.g., enhanced sampling and free energy calculations. Although applicable to a wide variety of research problems, a broader usage of MD is hindered by a steep initial learning curve imposed by nearly every MD software. To reduce this initial barrier and make the methodology more accessible to the general community of biomolecular researchers, we developed an intuitive tool named QwikMD (1), which assists the users in the preparation, execution, and analysis of biomolecular MD simulations. Among many other features, QwikMD automatically checks the initial structure for structural inconsistencies, facilitates structure manipulations such as point mutations and partial deletions, simplifies the protein insertion in lipid membranes and enables the visualization and analysis of MD simulations on the fly. The user-friendly graphical interface of QwiKMD allows the preparation of MD simulations in a point-and-click fashion, offering the user multiple MD protocols, such as unbiased MD simulations, Steered MD, MD Flexible Fitting (MDFF), and, most recently, hybrid QM/MM simulations. The latter exploits the recently developed VMD and NAMD interface to common quantum mechanics software packages. QwikMD facilitates performing MD simulations for nearly any user, novice or expert. While assisting the user, QwikMD ensures reproducibility of the results by recording all parameters and steps into two log files, one in a script-like format and another in a “methods section” format. QwikMD also serves as a learning tool, providing the theoretical background of the different MD protocols and options in many “info buttons”.

Halogen bonds (XBs) are non-covalent R–X∙∙∙B interactions where heavy halogens (X = Cl, Br, I) act as electrophilic species interacting with Lewis bases (B). This highly directional type of interaction is mostly explained by the existence of a positive region on the molecular electrostatic potential located at the tip of the halogen (called σ-hole), arising from polarization of the R–X covalent bond. Following the recognition of the significance of XBs in biomolecular structures [1], their application in rational drug design, amongst other areas, has been increasingly explored. In this context, the development of computational tools accurately modelling XB is of paramount importance. This is particularly challenging in the case of force field (FF)-based methods, where XBs are typically modelled by introducing a positive extra-point (EP) of charge to mimic the σ-hole [2]. Though different schemes for EP parameterization have been proposed for AMBER or other FFs, their application to lengthy molecular dynamics (MD) simulations is still uncommon. In this work, we assessed the performance of distinct EP models and their transferability to the popular united-atom GROMOS FF, using bacteriophage T4 Lysozyme as a prototype system. The L99A mutant of this enzyme contains a large non-polar cavity that binds iodobenzene and related ligands, via XBs [3]. MD simulations were carried out and the network of intermolecular interactions, particularly XBs targeting different acceptors in the protein, was analysed. The results showed the dramatic impact of varying the X–EP distance and the associated sets of charges on the description of XBs. This, together with the implications for computer-aided drug design will be discussed [4].

Acknowledgements:Support for this work was provided by FCT through UID/MULTI/00612/2013 and IF/00069/2014. R.N. acknowledges financial support from PhD scholarship SFRH/BD/116614/2016.

Alkaloids of the canthi-6-one type have been reported in differents natural sources. These alkaloids have showed a wide range of pharmacological properties including cytotoxic, antibacterial, antifungal, antiparasict, antiviral, anti-inflammatory and beside it, some of them show excellent photophysical properties that gives an interesting use as fluorescent dye probe in florescent cellular microscopy. Because it, new studies have been carrying out in an attempt to identify new alkaloids with pharmacological properties. Some researchers have been trying to synthesize new derivatives or identify new compounds in natural sources. Among the >60 canthin-6-one alkaloids already reported in natural sources, more the half are present in plants of the family Simaroubaceae. In the Simaba genus, up to the present, only eighteen alkaloids was described in seven species, but other plants of the genus that occur in the brazilian’s flora haven’t been studied yet. In this work we describe the first phytochemical study of the specie Simaba bahiensis (Simaroubaceae), collected at the city of Camaçari, Bahia State, Brazil. Also, it’s related complete structural determination using differents NMR experiments and HRMS of a new canthin-6-one alkaloid in addition to two others already known.

The genus Stillingia (Euphorbiaceae) is represented by 30 species distributed in the America and islands of the Pacific. In Brazil, seven species are distributed between Caatinga and Atlantic Forest, four of which are predominantly Caatinga. Only four species of Stillingia were studied chemically. Diterpenes with rare flexibilane skeletons have been reported from the roots of S. sanguinolenta. These compounds demonstrated interesting pharmacological activities. The use of hyphenated techniques, such as LC-MS2, coupled with bioinformatics techniques such as Molecular Networking, are able to rapidly identify substances from complex biological extracts. Thus, the objective of the study was the identification of flexibilene diterpenes, using LC-MS2 and Molecular Networking, of root bark of S. loranthaceae. The botanical identification was carried out in the Herbarium Alexandre Leal Costa at the Biology Institute of UFBA. The hexane extract (HE) from the root bark was analyzed by LC-MS2, and the data were used to generate a molecular network in GNPS site. It was possible to observe a cluster represent this diterpene skeleton in the molecular network. This data associated to MS/MS fragmentation approach suggested the presence of several new flexibilene diterpenes and known compounds (tonantzitlolone A-C) already identified from other Stillingia species.

In this paper, a multilinear regression (MLR) analysis has been carried out in order to accurately predict physicochemical properties and biological activities on a group of antibacterial quinolones by means of a set of structural descriptors called topological indices. The aim of this work is to develop prediction equations for these properties after collecting the maximum number of data from the literature on antibacterial quinolones.

Structural Health Monitoring is aimed at transforming civil structures into self-diagnosing systems able to automatically reveal the occurrence of a fault or a damage after a critical event such as an earthquake. While data science is presently experiencing a tremendous development, leading to the availability of powerful tools and algorithms that extract relevant information by effectively fusing data provided by different types of sensors, one of the main bottlenecks still limiting the development of SHM in the filed of civil engineering is the general lack of reliable sensing technologies that are effectively applicable to the large scale. A very promising solution to such a large scale challenge would be using the same construction materials for strain sensing and direct damage detection. In this view, the authors have recently proposed smart concretes and smart bricks that are piezoresistive concretes and clay bricks obtained by doping traditional construction materials with conductive nano- or micro inclusions. These novel multifunctional materials have the ability to provide measurable electrical output under application of a mechanical load and to provide information useful for damage detection, localization and quantification. The paper introduces both technologies, discusses their potentials and illustrates their application to paradigmatic structural elements arranged in the laboratory. The presented results contribute to showing the revolutionary impact that smart concretes and smart bricks may have in the near future on SHM of concrete and masonry structures.

The use of low-cost transducers such as piezoelectric diaphragms in structural health monitoring (SHM) applications based on the electromechanical impedance (EMI) method has grown in recent years. Although many studies report the feasibility of such transducers for impedance-based damage detection, the experiments are typically performed on small structures. Therefore, the objective of this work is to perform an experimental analysis of the feasibility of the piezoelectric diaphragms for the detection of damage in large structures. Several tests were carried out on a large aluminum plate in which a diaphragm was attached. The electrical impedance signatures of the transducer were collected and a basic damage index was calculated in order to verify the feasibility of quantifying the size of the damage at different distances from the transducer. The experimental results indicate that the piezoelectric diaphragms have a good sensitivity to provide a damage size classification in large structures. In addition, the sensitivity to damage detection and classification decrease as the distance between the transducer and the damage increases. Therefore, the results reported in this study indicate that low-cost piezoelectric diaphragms are feasible for impedance-based SHM applications in large structures.

The possibility of using mobile devices, such as smartphones, for locating a person indoor is becoming more attractive for many applications. Among them are health care and safety services, commercial and emergency applications. One of the approaches to find the smartphone position is known as Pedestrian Dead Reckoning (PDR). PDR relies on the smartphone low-cost sensors, such as accelerometers, gyroscopes, barometer and magnetometers. An appropriate calibration phase to find the step length algorithm gains is required before PDR can be applied. These gains are very sensitive to the user and smartphone mode. In this research, we employ machine learning classifications algorithms in order to recognize and classify the pedestrian and smartphone modes. A methodology of training on a single user and testing on multiple users is proposed and experimentally evaluated. Results show successes in classifying the user and smart phone modes.

Droughts have been poorly studied in Estonia despite of the important water deficit that occurred in recent times e.g. 2002 and 2006. We have studied the influence of atmospheric indices on the spatial and temporal variability of droughts in Estonia. We have analyzed 57 monthly precipitation series and 7 atmospheric indices (NAO, EA, EATL/WRUS, SCAND, P/EU, AO and WI) during the period 1951-2015. Estonia has been regionalized in three homogeneous regions according to drought variability, i.e. western, southeastern and northern. Standardized precipitation index at timescale of 1, 3, 6, and 12 months have been computed for each region. From 1951 to 1977 dry conditions prevail. On the other hand, from 1978 to 2015 wet conditions prevail interrupted by some intense but short droughts. The main influence of atmospheric indices on drought variability is recorded with SCAND for spring and autumn (negative correlations) and with WI for winter and summer (positive correlations).

Atmospheric evaporative demand (ADE) trends at global scale are important to understand the impact of global warming in the hydrological cycle. But there is no consensus, in the global scale studies, about ADE variability and many areas have been ignored in regional studies. This is the case of Estonia, located in theeastern coast of the Baltic Sea between 57.5 and 59.5°N. To shed light on the ADE variability in the country we have studied the spatial and temporal variability of ET0 from 1951 to 2015.

We have computed ET0 from 9 high-quality meteorological stations by Penman–Monteith equation. We have analysed the spatial and temporal variability of ET0 and its main drivers i.e. maximum temperature, minimum temperature, wind speed, sunshine duration, relative humidity and atmospheric pressure.

ET0, at annual scale and country level, shows a positive and significant trend with a magnitude of change during the studied period of 5.3 mm decade-1, with the highest values during the spring (4.1 mm decade-1). The costal series show a higher magnitude of change (7.1 mm decade-1in average) than the inland series (4.3 mm decade-1 in average), principally because coastal areas show greater magnitude of change during the summer. High significant correlation (r=0.7-0.8) have been found among computed ET0and observed evaporation measurements with evaporation pan and lysimeter during the period 1968-2005.

At annual scale, during spring and summer ET0 is highly correlated with sunshine (positive), relative humidity (negative) and maximum temperature (positive). Meanwhile sunshine has no significate trend, maximum temperature shows positive and significant trend in all the series and seasons and relative humidity shows significant negative trends in 8 of the 9 series studied during the spring.